RESUMEN
The precise determination of photosynthetic pigment content in green organisms, chlorophylls (Chls) and carotenoids (Cars), is important to investigate many photosynthetic processes such as responses to environmental fluctuations or to gene mutations, as well as to interpret biochemical and structural results obtained on purified membranes and photosynthetic complexes. The most utilized methods for determination by spectrophotometry of Chl content in solution, usually 80% acetone, are based on the use of simultaneous equations. The advantages are the easiness and speed over chromatography, which also requires less common equipment. The disadvantage is that issues in sample preparation or in the measurement are not detectable, which could lead to wrong results. Here we propose a fast, accurate and (almost) error-proof method to measure Chl a, Chl b and also total Car content in a solution of pigments extracted from tissue, membranes or purified complexes. The method is based on the fit of the absorption spectrum of the acetone extract using the spectra of purified pigments as references. We show how this method allows a more precise and accurate estimation of pigment content as compared to classical equations, even in incorrectly prepared acetone solutions. Moreover, the method allows the discovery of artifacts in sample preparation or measurement and thus drastically reduces the risk of mistakes. Examples obtained on purified complexes are also discussed. Based on newly acquired Chl spectra, we also propose a new set of improved simultaneous equations that provide slightly different but more reliable results in comparison with the currently used equations.
Asunto(s)
Clorofila , Proteínas del Complejo del Centro de Reacción Fotosintética , Carotenoides/metabolismo , Clorofila/análisis , Clorofila A , FotosíntesisRESUMEN
Phages are the most abundant biological entities on the planet, and they play an important role in controlling density, diversity, and network interactions among bacterial communities through predation and gene transfer. To date, a variety of bacteriophage identification tools have been developed that differ in the phage mining strategies used, input files requested, and results produced. However, new users attempting bacteriophage analysis can struggle to select the best methods and interpret the variety of results produced. Here, we present MetaPhage, a comprehensive reads-to-report pipeline that streamlines the use of multiple phage miners and generates an exhaustive report. The report both summarizes and visualizes the key findings and enables further exploration of key results via interactive filterable tables. The pipeline is implemented in Nextflow, a widely adopted workflow manager that enables an optimized parallelization of tasks in different locations, from local server to the cloud; this ensures reproducible results from containerized packages. MetaPhage is designed to enable scalability and reproducibility; also, it can be easily expanded to include new miners and methods as they are developed in this continuously growing field. MetaPhage is freely available under a GPL-3.0 license at https://github.com/MattiaPandolfoVR/MetaPhage. IMPORTANCE Bacteriophages (viruses that infect bacteria) are the most abundant biological entities on earth and are increasingly studied as members of the resident microbiota community in many environments, from oceans to soils and the human gut. Their identification is of great importance to better understand complex bacterial dynamics and microbial ecosystem function. A variety of metagenome bacteriophage identification tools have been developed that differ in the phage mining strategies used, input files requested, and results produced. To facilitate the management and the execution of such a complex workflow, we developed MetaPhage (MP), a comprehensive reads-to-report pipeline that streamlines the use of multiple phage miners and generates an exhaustive report. The pipeline is implemented in Nextflow, a widely adopted workflow manager that enables an optimized parallelization of tasks. MetaPhage is designed to enable scalability and reproducibility and offers an installation-free, dependency-free, and conflict-free workflow execution.